Midjourney V7 Amelioration
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-enhance",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-enhance",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: 'mj-v7-enhance',
model_params: {task_id: 'task-unified-xxx', image_number: 0}
})
};
fetch('https://api.evolink.ai/v1/images/generations', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.evolink.ai/v1/images/generations",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'model' => 'mj-v7-enhance',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 0
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.evolink.ai/v1/images/generations"
payload := strings.NewReader("{\n \"model\": \"mj-v7-enhance\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.evolink.ai/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"mj-v7-enhance\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.evolink.ai/v1/images/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"model\": \"mj-v7-enhance\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0\n }\n}"
response = http.request(request)
puts response.read_body{
"created": 1757165031,
"id": "task-unified-1757165031-mjv7",
"model": "<string>",
"object": "image.generation.task",
"progress": 0,
"status": "pending",
"task_info": {
"can_cancel": true,
"estimated_time": 45
},
"type": "image",
"usage": {
"billing_rule": "per_call",
"credits_reserved": 1.8,
"user_group": "default"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}Midjourney V7
Midjourney V7 Amélioration
- Ameliore les brouillons generes en mode draft a une qualite standard
- Flux de travail recommande : d’abord utiliser mj-v7 + mode draft pour un apercu rapide a faible cout, puis ameliorer une fois satisfait
- Prend uniquement en charge les taches source generees en mode draft
- Mode de traitement asynchrone, utilisez l’ID de tache retourne pour effectuer une requete
POST
/
v1
/
images
/
generations
Midjourney V7 Amelioration
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-enhance",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-enhance",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: 'mj-v7-enhance',
model_params: {task_id: 'task-unified-xxx', image_number: 0}
})
};
fetch('https://api.evolink.ai/v1/images/generations', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.evolink.ai/v1/images/generations",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'model' => 'mj-v7-enhance',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 0
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.evolink.ai/v1/images/generations"
payload := strings.NewReader("{\n \"model\": \"mj-v7-enhance\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.evolink.ai/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"mj-v7-enhance\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.evolink.ai/v1/images/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"model\": \"mj-v7-enhance\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0\n }\n}"
response = http.request(request)
puts response.read_body{
"created": 1757165031,
"id": "task-unified-1757165031-mjv7",
"model": "<string>",
"object": "image.generation.task",
"progress": 0,
"status": "pending",
"task_info": {
"can_cancel": true,
"estimated_time": 45
},
"type": "image",
"usage": {
"billing_rule": "per_call",
"credits_reserved": 1.8,
"user_group": "default"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}{
"error": {
"code": "<string>",
"message": "<string>",
"type": "<string>"
}
}Midjourney dispose d’un système de modération de contenu intégré. Si certaines images générées sont filtrées par la modération, les crédits consommés pour cette requête ne seront pas remboursés. Veuillez vous assurer que vos prompts respectent les directives de contenu.
Autorisations
##Toutes les interfaces necessitent une authentification par Bearer Token##
Obtenir une cle API :
Visitez la page de gestion des cles API pour obtenir votre cle API
Ajoutez dans l'en-tete de la requete :
Authorization: Bearer YOUR_API_KEY
Corps
application/json
Réponse
Tâche créée avec succès
Horodatage de création
Exemple:
1757165031
ID de la tâche
Exemple:
"task-unified-1757165031-mjv7"
Nom du modèle utilisé
Type de tâche
Options disponibles:
image.generation.task Pourcentage de progression (0-100)
Plage requise:
0 <= x <= 100Exemple:
0
Statut de la tâche
Options disponibles:
pending, processing, completed, failed Exemple:
"pending"
Show child attributes
Show child attributes
Options disponibles:
text, image, audio, video Exemple:
"image"
Show child attributes
Show child attributes